Chitra Devi A
Date d'abonnement : 2022
Ligue d'Argent
4860 points
Gemini in Google Meet
Earned jan. 22, 2024 EST
Gemini in Google Sheets
Earned jan. 22, 2024 EST
Gemini in Google Slides
Earned jan. 22, 2024 EST
Gemini in Google Docs
Earned jan. 22, 2024 EST
Gemini in Gmail
Earned jan. 20, 2024 EST
Google Workspace with Gemini: Foundations of Your AI Workflow
Earned jan. 20, 2024 EST
[DEPRECATED] Generative AI Fundamentals
Earned sept. 19, 2023 EDT
[DEPRECATED]Introduction to Responsible AI
Earned juin 22, 2023 EDT
Introduction to Large Language Models
Earned juin 22, 2023 EDT
Encoder-Decoder Architecture
Earned juin 22, 2023 EDT
Introduction to Generative AI
Earned juin 22, 2023 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned mai 18, 2023 EDT
How Google Does Machine Learning
Earned avr. 27, 2023 EDT
Machine Learning Operations (MLOps): Getting Started
Earned avr. 23, 2023 EDT
This course covers how to use Gemini in Google Meet to enhance video collaboration. Learn to automate note-taking, utilize real-time text and speech translation, privately catch up on missed discussions, and instantly optimize your audio and video quality. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course covers how to use Gemini in Google Sheets to automate data organization and crunch complex numbers. Learn to structure tables from raw text, auto-populate data using natural language, generate native spreadsheet formulas on demand, and rapidly extract high-level insights or visualizations without needing advanced spreadsheet expertise. Explore other content in the Gemini Agent Ready (GEAR) program.
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This course covers how to use Gemini in Google Slides to transform concepts into visually compelling presentations. Learn to generate structured decks from a single prompt or existing source document, refine slide layouts using automated design enhancement, create custom vector graphics and photos, and dynamically craft on-slide copy alongside precise speaker notes.
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This course covers how to use Gemini in Google Docs to streamline your writing and content creation. Learn to draft documents from scratch, refine writing tone and clarity with interactive tools, summarize complex files, and seamlessly transform long-form text into structured assets for other Google Workspace applications. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course covers how to use Gemini in Gmail to optimize your email management. Learn to summarize lengthy threads, retrieve information using natural language, draft professional responses, and organize communication strategies directly inside your inbox. Explore other content in the Gemini Agent Ready (GEAR) program.
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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. Here, you will learn about the key features of Gemini and how they can be used to improve productivity and efficiency. Continue building your skills in the full Google Workspace with Gemini learning path, and explore other content in the Gemini Agent Ready (GEAR) program.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Explore other content in the Gemini Agent Ready (GEAR) program.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.
The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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